Gemma 3 12B vs Tencent Hunyuan Turbo S
Gemma 3 12B (2026) and Tencent Hunyuan Turbo S (2026) are compact production models from Google DeepMind and Tencent AI Lab. Gemma 3 12B ships a 33k-token context window, while Tencent Hunyuan Turbo S ships a 200k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Tencent Hunyuan Turbo S fits 6x more tokens; pick it for long-context work and Gemma 3 12B for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemma 3 12B | Tencent Hunyuan Turbo S |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Classification and JSON / Tool use | Long context |
| Context window | 33k | 200k |
| Cheapest output | $0.13/1M tokens | - |
| Provider routes | 5 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3 12B has broader tracked provider coverage for fallback and procurement flexibility.
- Gemma 3 12B uniquely exposes Structured outputs in local model data.
- Local decision data tags Gemma 3 12B for Classification and JSON / Tool use.
- Tencent Hunyuan Turbo S has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Tencent Hunyuan Turbo S for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 3 12B
$64.50
Cheapest tracked route/tier: OpenRouter
Tencent Hunyuan Turbo S
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 3 12B and Tencent Hunyuan Turbo S; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Tencent Hunyuan Turbo S and Gemma 3 12B; plan for SDK, billing, or endpoint changes.
- Gemma 3 12B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-01-01 | 2026-01-10 |
| Context window | 33k | 200k |
| Parameters | 12B | — |
| Architecture | decoder only | - |
| License | Gemma | Tencent Hunyuan Community License |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2024-08 | - |
Pricing and availability
| Pricing attribute | Gemma 3 12B | Tencent Hunyuan Turbo S |
|---|---|---|
| Input price | $0.04/1M tokens | - |
| Output price | $0.13/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Gemma 3 12B | Tencent Hunyuan Turbo S |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Gemma 3 12B. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: Gemma 3 12B has $0.04/1M input tokens and Tencent Hunyuan Turbo S has no token price sourced yet. Provider availability is 5 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 3 12B when provider fit and broader provider choice are central to the workload. Choose Tencent Hunyuan Turbo S when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Gemma 3 12B or Tencent Hunyuan Turbo S?
Tencent Hunyuan Turbo S supports 200k tokens, while Gemma 3 12B supports 33k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 3 12B or Tencent Hunyuan Turbo S open source?
Gemma 3 12B is listed under Gemma. Tencent Hunyuan Turbo S is listed under Tencent Hunyuan Community License. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Gemma 3 12B or Tencent Hunyuan Turbo S?
Gemma 3 12B has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemma 3 12B and Tencent Hunyuan Turbo S?
Gemma 3 12B is available on Cloudflare Workers AI, AWS Bedrock, OpenRouter, GCP Vertex AI, and Novita AI. Tencent Hunyuan Turbo S is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3 12B over Tencent Hunyuan Turbo S?
Tencent Hunyuan Turbo S fits 6x more tokens; pick it for long-context work and Gemma 3 12B for tighter calls. If your workload also depends on provider fit, start with Gemma 3 12B; if it depends on long-context analysis, run the same evaluation with Tencent Hunyuan Turbo S.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.